Preferred Name

Chi Hang Au

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


Date of Graduation

Summer 2018

Document Type


Degree Name

Master of Arts (MA)


Department of Graduate Psychology


Allison J. Ames


Posterior predictive model checks (PPMC) are one Bayesian model-data fit approach. Thus far, PPMC for Confirmatory Factor Analytic applications focused primarily on global fit evaluation, ignoring the nuanced information in local misfit diagnostics. This study developed a PPMC approach for local misfit and applied it to a test-taking motivation scale. If the PPMC approach is effective, fit conclusions derived from the PPMC approach should be congruent with the fit conclusions derived from the Frequentist approach. Number of item-pairs flagged as misfitting and number of disagreements were computed to evaluate congruence. Congruence is achieved if the number of item-pairs flagged as misfitting is equivalent under the Frequentist and the Bayesian approach and the number of disagreements is zero. Although congruence was not achieved, the present research sets up foundation for future research in PPMC.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.